Biologically agglutinated eukaryotic microfossil from Cryogenian cap carbonates

Cryogenian cap carbonates that overlie Sturtian glacial deposits were formed during a post‐glacial transgression. Here, we describe microfossils from the Kakontwe Formation of Zambia and the Taishir Formation of Mongolia—both Cryogenian age, post‐Sturtian cap carbonates—and investigate processes involved in their formation and preservation. We compare microfossils from these two localities to an assemblage of well‐documented microfossils previously described in the post‐Sturtian Rasthof Formation of Namibia. Microfossils from both new localities have 10 ± 1 μm‐thick walls composed of carbonaceous matter and aluminosilicate minerals. Those found in the Kakontwe Formation are spherical or ovoid and 90 ± 5 μm to 200 ± 5 μm wide. Structures found in the Taishir Formation are mostly spherical, 50 ± 5 μm to 140 ± 5 μm wide, with distinct features such as blunt or concave edges. Chemical and mineralogical analyses show that the walled structures and the clay fraction extracted from the surrounding sediments are composed of clay minerals, especially muscovite and illite, as well as quartz, iron and titanium oxides, and some dolomite and feldspar. At each locality, the mineralogy of the microfossil walls matched that of the clay fractions of the surrounding sediment. The abundance of these minerals in the walled microfossils relative to the surrounding carbonate matrix and microbial laminae, and the presence of minerals that cannot precipitate from solution (titanium oxide and feldspar), suggests that the composition represents the original mineralogy of the structures. Furthermore, the consistency in mineralogy of both microfossils and sediments across the three basins, and the uniformity of size and shape among mineral grains in the fossil walls indicate that these organisms incorporated these minerals by primary biological agglutination. The discovery of new, mineral‐rich microfossil assemblages in microbially laminated and other fine‐grained facies of Cryogenian cap carbonates from multiple localities on different palaeocontinents demonstrates that agglutinating eukaryotes were widespread in carbonate‐dominated marine environments in the aftermath of the Sturtian glaciation. Keywords: microfossil, agglutinated, tests, Cryogenian, Sturtian, Kakontwe, TaishirSmith College (Tomlinson Fund)Smith College. Geosciences DepartmentNASA Astrobiology Institut

Tuning Electrical, Optical, and Thermal Properties through Cation Disorder in Cu2ZnSnS4

Chemical disorder in semiconductors is important to characterize reliably because it affects materials performance, for instance by introducing potential fluctuations and recombination sites. It also represents a means to control material properties, to far exceed the limits of equilibrium thermodynamics. We present a study of highly disordered Cu-Zn-Sn-S (d-CZTS) films along the Cu2SnS3-Cu2ZnSnS4-ZnS binary line, deposited by physical vapor deposition. Deposition at low temperature kinetically stabilizes compositions that are well outside of the narrow, equilibrium solid solution of kesterite (Cu2ZnSnS4). Here we study d-CZTS and its thermal treatment using complementary characterization techniques: X-ray absorption spectroscopy (XAS), X-ray diffraction (XRD), and transmission electron microscopy (TEM). We find that cations in d-CZTS are highly disordered while the sulfur anions remain in a well-defined, cubic close-packed lattice. On the atomic scale, composition fluctuations are accommodated preferentially by stacking faults. Kinetically-stabilized cation disorder can produce nonequilibrium semiconductor alloys with a wide range of band gap, electronic conductivity, and thermal conductivity. d-CZTS therefore represents a processing route to optimizing materials for optoelectronic device elements such as light absorbers, window layers, and thermal barriers.Army Research Office (Grant W911NF-16-1-0406

Fast and interpretable classification of small X-ray diffraction datasets using data augmentation and deep neural networks

© 2019, The Author(s). X-ray diffraction (XRD) data acquisition and analysis is among the most time-consuming steps in the development cycle of novel thin-film materials. We propose a machine learning-enabled approach to predict crystallographic dimensionality and space group from a limited number of thin-film XRD patterns. We overcome the scarce data problem intrinsic to novel materials development by coupling a supervised machine learning approach with a model-agnostic, physics-informed data augmentation strategy using simulated data from the Inorganic Crystal Structure Database (ICSD) and experimental data. As a test case, 115 thin-film metal-halides spanning three dimensionalities and seven space groups are synthesized and classified. After testing various algorithms, we develop and implement an all convolutional neural network, with cross-validated accuracies for dimensionality and space group classification of 93 and 89%, respectively. We propose average class activation maps, computed from a global average pooling layer, to allow high model interpretability by human experimentalists, elucidating the root causes of misclassification. Finally, we systematically evaluate the maximum XRD pattern step size (data acquisition rate) before loss of predictive accuracy occurs, and determine it to be 0.16° 2θ, which enables an XRD pattern to be obtained and classified in 5.5 min or less

Acid‐in‐Clay Electrolyte for Wide‐Temperature‐Range and Long‐Cycle Proton Batteries

Proton conduction underlies many important electrochemical technologies. A family of new proton electrolytes is reported: acid-in-clay electrolyte (AiCE) prepared by integrating fast proton carriers in a natural phyllosilicate clay network, which can be made into thin-film (tens of micrometers) fluid-impervious membranes. The chosen example systems (sepiolite-phosphoric acid) rank top among the solid proton conductors in terms of proton conductivities (15 mS cm-1 at 25 °C, 0.023 mS cm-1 at -82 °C), electrochemical stability window (3.35 V), and reduced chemical reactivity. A proton battery is assembled using AiCE as the solid electrolyte membrane. Benefitting from the wider electrochemical stability window, reduced corrosivity, and excellent ionic selectivity of AiCE, the two main problems (gassing and cyclability) of proton batteries are successfully solved. This work draws attention to the element cross-over problem in proton batteries and the generic "acid-in-clay" solid electrolyte approach with superfast proton transport, outstanding selectivity, and improved stability for room- to cryogenic-temperature protonic applications